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Transforming E&P Applications through Big Data Analytics

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Course Credit: 0.15 CEU, 1.5 PDH

Data Driven Analytics in the Upstream Oil and Gas Industry
Shahab D. Mohaghegh
When it comes to data driven analytics there seem to be more questions than there are answers. This is quite natural when a novel technology tries to find its rightful place in a well-established industry. In this section of this three-part presentation, we attempt to address the questions that usually arise by petroleum professionals when data driven analytics is brought up. The objective is to clarify some of the confusion that seem to be surrounding the practical and useful implementation this technology in the upstream oil and gas industry.
The questions that will be addressed are: What is Data-Driven Analytics / Data Analytics? What are the main components of this technology? Who should be the owners and the champions of Data-Driven Analytics in a company? Is this an IT related technology or is more related to drilling, completion, geosciences, reservoir and production engineering? What are the commonalities and differences between the application of this technology in the oil and gas industry as compared to other industries? Who are the main players? What expertise are required? What is the relationship between Data-Driven Analytics and Physics? Is it really a black box? How does “Big Data” relate to data driven analytics? What is the manifestation of “Big Data” in our industry? How should this technology be incorporated in the operating companies? Who are the vanguards in our industry? Why is the academia not involved?

Geoscience Data Analytics: What can it do for me?
Dr. Srikanta Mishra
“Data analytics” has become quite the buzzword in recent years across a multitude of disciplines ranging from marketing to science and engineering. It involves analyzing data using advanced statistical methods to understand hidden patterns of association and input-output relationships in large, complex, multivariate data sets. The field of geoscience data analytics, i.e., the application of data analytics in E&P operations, is also emerging as an exciting new development. In this talk, I will provide an overview of various data analytics techniques that can be applied to understand “what the data say” in the context of oil and gas operations. Examples from reservoir characterization, production evaluation and reservoir performance will be used to demonstrate the applicability of these techniques and their potential for extracting data-driven insights as an aid to improved decision making.

Exploiting data value in real-time upstream production operations
Dr. Luigi Saputelli
To increase the opportunities for profitability, upstream operators have deployed sophisticated hardware for remote sensing and actuation of wells and facilities. However, efficient transformation of data acquisition into value-added actions still a challenge. Assimilation of real time data offer unique advantages in answering crucial questions for improving asset performance. The combination of data-driven predictive analytics, large computer power and multidimensional data visualization propose opportunities for discovering deep knowledge previously hidden by traditional engineering and statistical methods. During the last decades, a number of predictive models, from outside E&P industry, have been adapted to upstream production and real-time data surveillance. Typical real-time production applications include reservoir model response, virtual metering and soft sensing. In this presentation, some success stories using linear time series, neural networks, fuzzy logic and reduced order modeling will be displayed and analyzed. Key challenges and R&D requirements in applying data driven techniques in real-time data analysis will also be addressed.

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 1 chapter

Course Chapters

  • 1Transforming E&P Applications through Big Data Analytics - Chapter 1
    Media Type: Video

Credits

Earn credits by completing this course0.15 CEU credit1.5 PDH credits

Speakers

Srikanta Mishra
Dr. Luigi Saputelli
Dr. Shahab Mohaghegh